AI photo tagging that lives in your stack, not on a vendor's roadmap. Shipped from Washington.

Our goal is to give Seattle businesses a three-day weekend, so people can spend more time with their families and the people they love :)

Seattle businesses don't need another generic AI pitch. AI photo tagging only earns its keep when it's built around the workflow you actually run on a wet Tuesday, and that's how we scope every engagement we take on in Washington.

What AI photo tagging actually does

Job-site photos, property listings, product shots, before/afters - auto-tagged, captioned, and filed in seconds. Search your photo library like it's a database.

  • 01 Auto-tag with content, room, defect, or product type
  • 02 Generates listing captions and alt text for SEO
  • 03 Detects safety hazards in site photos
  • 04 Filing into your DAM, project tool, or Drive

Built on: Claude Vision Replicate Cloudinary Vercel

What you actually get

Every engagement is scoped and quoted up front. This is what is in the box.

How AI photo tagging compares

The two things most businesses do instead, and where each one runs out.

 Hiring for itAn off-the-shelf toolKiwi Dynamics
Fit to how you workFits perfectly, costs a salaryYou bend your process to suit the toolBuilt around the workflow you already run
Time to something usefulImmediate, and permanentQuick to switch on, slow to make fitA working slice in weeks, then hardened
Who owns the dataYou doThe vendor, on the vendor's termsYou do, in your own accounts
When it breaksThat person sorts it, if they are inA support queue and a ticket numberThe people who built it
What it costsA salary, every year, foreverPer seat, forever, used or notScoped and quoted up front

What we keep seeing in Seattle.

  • Seattle runs on cloud computing, aerospace and coffee, home to the companies whose infrastructure half the internet's AI runs on - AI here means holding up to serious technical scrutiny.
  • Two of the world's largest cloud providers are headquartered here alongside a major aerospace manufacturing base. Seattle businesses, even small ones, tend to have someone on staff who can and will check your work.

We work with teams across Seattle: Downtown Seattle · Capitol Hill · Bellevue · Fremont · Ballard · Redmond.

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How we build AI photo tagging for a Seattle team.

We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Seattle business, so value lands before the build is finished. AI vision + tagging.

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How the work runs

The outcome for Seattle teams

The shape of the result for Seattle teams: Photo admin time cut from hours per week to minutes. Built on Claude Vision, hardened with the rest of the stack as it scales.

Not your typical AI agency.

Honest about what AI can and cannot do

Ships the one workflow that pays for itself

Hours given back, never the size of the invoice

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*Every engagement is scoped and quoted up front. Results vary by workflow and business.

How much is not automating costing you?

Nine hours a week of admin is 468 hours a year. With Kiwi Dynamics, that drops to about 52.

Try the calculator

*Based on 9 hours a week of admin at Kiwi Dynamics' typical 80% automation rate. Your number may vary, the calculator uses your own.

FAQ

What's the realistic timeline for AI photo tagging with a Seattle?

Most Seattle businesses have their first usable slice in week 5 or 6. We'd rather ship narrow and real than broad and aspirational - your team gets to use the thing well before the engagement is "done".

What does AI photo tagging cost for a Seattle?

Pilots start from a fixed scope priced to land a measurable result inside 6 weeks. Pricing depends on data volume, integration complexity, and whether you need us on managed services afterwards. We'll quote precisely after a 30-minute scoping call.

Can you walk us through a comparable build?

Yes - on the first call we'll pick the closest engagement we've shipped to what you're describing and walk through the outcome, the headcount and the time it took. Photo admin time cut from hours per week to minutes.

What happens if we want to swap a vendor out later?

AI photo tagging is built behind a small adapter layer specifically so swapping a model provider or a data source is a one-day job, not a re-architecture. Claude Vision, Replicate, Cloudinary, Vercel are our defaults, but the build is intentionally portable.

Twenty minutes, your call.

You describe what's broken. We'll tell you what we'd actually do about it.

Talk to us about this

Tell us what you're trying to do and we'll reply with how we'd build it - no obligation.